Analytics and Business Intelligence Overview

What Is The Flow Analytics Framework?

The Flow Analytics framework is the single most powerful data analysis framework available today.

Flow allows you to design workflows which can solve and automate any data analysis challenge irrespective of scale or complexity.

Flow facilitates the end-to-end data analytics pipeline. Flow can access and consolidate data from any required sources, cleanse and prepare data
faster than any other technology, perform advanced analytics, and provides a structured framework for the communication of analysis results to decision makers.

Flow is capable of:

Accessing Data from any source

Cleansing and transforming data

Deriving new data points through expressions

Calculating statistics

Performing multidimensional analysis

Summarizing and describing data

Computing hypercubes

Designing multidimensional reports

Aggregating and analyzing social feeds

Automating any data analysis workflow

Performing advanced AI

Connecting to Watson and Cortana

Delivering Dashboards

Generating and distributing reports

Analyzing unstructured data

Autonomous cognitive computation

Training machine learning models

Time series forecasting and prediction

Interpolating and extrapolating

Automating data analytics

Delivering analysis results

Distributed computing

Charting and visualizing data

Solving any data analysis problem

A Business-Oriented Data Analysis Framework

Most technologies for performing data analytics (such as R or Python) were not built with business in mind. Flow provides a computational engine equivalent to anything
that can be done with code, but is also a framework developed specifically for bridging the gap between computational data analysis power and the delivery of actionable
results to business decision makers.

Flow focuses on analysis workflows producing results. The construct of results in the system ensures that data analysis workflows are structured to have clear output.
Flow provides infrastructure for communicating analysis results to decision makers and for automating the delivery of data and insights.

Flows business-oriented analysis framework allows you to:

Automate any data analytics task

Deliver actionable results through the cloud

Build any custom dashboard or view

Monitor all automations from the cloud

Eliminate the need for custom code

Communicate data across your organization

Design multidimensional reports

Eliminate any manual process

Connect to any database or data source

Share and collaborate on workflows

Easily communicate analysis logic

Automate the flow of data

Track and monitor any important KPI's

Automatically summarize your data

Reduce risk through automation

Use AI to drive decison making

Predict and forecast any variables required

Have access to timeley accurate information

Visualize your data in charts and graphs

Eliminate costs of data movement

Connect all of your businesses data

Scale your analytics workflows

Optimize your business operations

Save money and increase profitability

Faster & More Powerful Than Code

Flow's computational environment is more powerful and flexible than code. Code is often the go-to approach for solving truly tough data analysis problems.
For complex data analysis scenarios, most companies turn to custom coded solutions using technologies such as R or Python.

Flow provides a better approach to the development, deployment, and management of data analysis solutions than these types of technologies.
Flow's computational framework is what is called "Turing-complete". In computing theory, this essentially means that anything that can be done by writing code using a
traditional programming language - Flow is capable of doing as well.

Flow's Cloud Connect development environment supports the rapid design and deployment of highly custom analytics solutions through an entirely different
approach to computing. The development lifecycle of a data analysis workflow in Flow is on average 100x faster than attempting to architect an equivalent solution
with code.

Flow is also vastly superior to custom-coded solutions when it comes to ongoing management of workflows and adapting your solutions as business requirements change.
Flow can automate a solution to any data analysis problem. If you don't believe it we will prove it. Contact us for a demo
here.

Join, Merge, and Unify Data

High performance data analysis workflows require being able to quickly aggregate and join data from different sources. Flow supports a multitude of data denormalization
and set based operations which allow data to easily be linked and joined for analysis.

Flow allows users to perform any type of join, append, or lookup rapidly accelerating the time required to bring together data sets for analysis. Flow's generic computing
engine can scale to process datasets of any size.

Cleanse, Transform, and Compute

More than 90% of the work in data analytics is in the preparation and cleansing of data. Flow's data-point-in data-point-out generic expression evaluation engine
drastically reduces the time required to prepare data.

Any data quality rules, data point transformation, or required feature extraction can be done with Flow. Flow provides a vast library of mathematical expressions,
logical operations, time series calculations, text based functions, probability operations and more which can compute any required data point on the fly.

Flow provides a number of data quality and data validation summary functions, analysis of blanks, and descriptive statistic functionality which allow you to quickly
detect outliers and anomalies and gain detailed understanding of the landscape of your data.

Flow accelerates data cleansing and data preparation tasks by being upwards of 50x faster than competing script-based technologies like R or Python.

Flow's data transformation capabilities allow you to:

Clean and scrub data points

Build complex expressions

Extract and compute new data points

Automate data quality rules

Identify anomalies and outliers

Identify and eliminate bad data

Summarize and describe data

Standardize values and enforce uniformity

Join datasets for analysis

Flatten and rotate data

Deduplicate and fuzzy deduplicate

Eliminate missing or incomplete records

Slice, dice, and filter data

Sample data and test hypothesis

Normalize disparate data

Analyze and transform unstructured data

Process datasets of any size

Perform text and language analytics

Correlate and discover patterns

Design any algorithm

Eliminate the need for code

Perform hyperdimensional statistics

Interpolate and impute values

Automate all data transformation tasks

HyperCube Analytics Engine

At the core of Flow is a revolutionary hypercube computational engine. This native hypercube engine allows data to be linked and transformed into optimized objects for
multidimensional analysis. Hypercube analytics allow you to generate any report or view on-demand and to evaluate any computational expression or statistical calculation
in a multidimensional context against your data.

Flow's multidimensional hypercube objects also open vast new possibilities for advanced artificial intelligence and machine learning applications. Hypercube computation
and analysis actions are embedded into workflows and can be executed in an autonomous context. Flow agents are capable of computing, mantaining, and delivering hypercubes to the cloud to provide continuously updated reports, views and dashboards.

Hypercube computation and Flow's high performance multidimensional statistical engine drastically reduces the time required to summarize
data and deliver multidimensional reports. Flow is capable of doing all of this without requiring any speciailized IT resources or data warehouse infrastructure.

Flow's hypercube analytics engine allows you to:

Build hypercubes for optimized analytics

Compute across hypercubes

Calculate multidimensional statistics

Design drill-down drill-through views

Pivot and rotate data

Correlate across hypercubes

Create any report or view

Transform data in hyperspace

Perform multidimensional analysis

Fold and linearize data

Optimize across hypercubes

Solve any analytics challenge

Distribute hypercube computation

Invoke AI across hypercubes

Aggregate data across any dimension

Design and evaluate hypercube expressions

Gain powerful insights

Deliver hypercubes to the cloud

Design dashboards from hypercubes

Summarize data in any way

Create multidimensional visualizations

Unlock the power of autonomous hypercubes

Perform jagged computation

Link and connect all of your data

Cognitive Computing and Artificial Intelligence

Flow provides direct interfaces to the full IBM Watson and MS Cortana cognitive computing suites. Cognitive computation and artificial intelligence functions can be
embedded into workflows in order to evaluate powerful cognitive analytics. Flow's cognitive interfaces allow for analysis such as sentiment analysis, keyword extractions,
topic detections, image recognition, facial recognition and more to be used in your data analysis workflows.

Flow bridges the gap between business data access and these high powered artificial intelligence engines. Flow allows your business to immediately leverage these types of
cognitive functions against it's data without having to worry about technical configuration or code.

Flow's plug-and-play capability with these AI engines makes artificial intelligence practical for everyone. Flow completely eliminates the bottlenecks associated with
feeding data to these types of AI systems and allows your business to focus on AI implementation and results.

Cognitive analysis can be used in the context of autonomous workflows to create intelligent logic for processes running continuously on agents. These AI functions
can derive new cognitive data points from existing data which can then be leveraged to create next-level autonomous decision structures and to drive more accurate
predictive modeling techniques.

Learned predictive structures can be embedded into workflows and invoked in an autonomous context. This allows you to develop intelligent learned logic for your
workflows. Machine learning models can be called upon on demand to produce up to date predictions and classify new data.

Flow's machine learning functions allow you to:

Train neural networks

Train bayesian models

Train decision trees

Train support vector machines

Classify data in an autonomous context

Cluster data and discover patterns

Learn linear and logistic models

Predict and forecast any variables

Connect machine learning to any data source

Automate machine learning tasks

Combine machine learning, ai, and hypercubes

Embed learned structures into workflows

Evaluate and predict on demand

Monitor and detect anomalies

Use machine learning for data quality

Cluster and segment customers

Solve any predictive challenge

Forecast and extrapolate

Create intelligent automatons

Tap machine learning in integrations

Use machine learning to trigger events

Distribute machine learning across agents

Solve any data analytics challenge

Eliminate the need for code

Distributed Computing Framework

Flow's distributed agent architecture and Tesseract File System allow analytics workflows to be scaled across multiple environments. Clusters of machines can easily be
linked up using Flow agents to support multi-machine parallel computing. Agents can orchestrate tasks and communicate information through the cloud to synchronize their
data processing efforts.

Flow's parallel agent computing paradigm allows you to scale your analytics workflows to process data of any size. Flow's managed Agent Cloud environments allow you to
deploy data intensive workflows without having to worry about setup or complex technical configuration.

Deliver Analysis Results

Flow emphasizes the delivery of results. In Flow, workflows produce results. Flow provides a clear framework for delivery and communication of analysis results to
decision makers. Analysis results are easily grouped together into presentation-ready dashboards and reports.

Cloud Based Dashboards and Reports

Data analytics is not all about computational power, it is just as much about delivering and communicating analysis output in such a way that it can be easily interpreted
and used to drive informed decision making.

Flow provides a user-friendly cloud portal and dashboard design enviornment which allows data analysts to efficiently organize and communicate their analysis results.
Flow's dashboards and analysis results support a sharing and collaboration engine which makes it easy to distribute dashboards and reports across your organization.

Automate Everything

Every data analysis workflow developed in Flow can be deployed to execute autonomously on agents. Automating data analytics with Flow allows your business to schedule
critical analysis processes, reduce costs, and deliver continuous and up to date information to decision makers.